 Data Management
“Data Management” design considerations emerge when we consider the data management aspects of a complete workflow system. The amount of information available to us is literally exploding, and the value of data as an organizational assest is widely recognised. Otherwise, data can become a liability, with the cost of acquiring it and managing it far exceeding the value derived from it.
To get the most out of the large and complex datas, users require tools that simply the tasks of managing the data and extracting useful information. Since the objective of scientific experiments is to transform data in a meaningful way, to the user. A common approach is to model the input and user requirements of user components (schemas) as tables in a database system.
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